Show simple item record

AuthorSharif, Muhammad
AuthorAmin, Javaria
AuthorSiddiqa, Ayesha
AuthorKhan, Habib Ullah
AuthorMalik, Muhammad Sheraz Arshad
AuthorAnjum, Muhammad Almas
AuthorKadry, Seifedine
Available date2022-12-28T11:20:01Z
Publication Date2020-09-03
Publication NameIEEE Access
Identifierhttp://dx.doi.org/10.1109/ACCESS.2020.3021660
CitationSharif, M., Amin, J., Siddiqa, A., Khan, H. U., Malik, M. S. A., Anjum, M. A., & Kadry, S. (2020). Recognition of different types of leukocytes using YOLOv2 and optimized bag-of-features. IEEE Access, 8, 167448-167459.
ISSN2169-3536
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85102781945&origin=inward
URIhttp://hdl.handle.net/10576/37759
AbstractWhite blood cells (WBCs) protect human body against different types of infections including fungal, parasitic, viral, and bacterial. The detection of abnormal regions in WBCs is a difficult task. Therefore a method is proposed for the localization of WBCs based on YOLOv2-Nucleus-Cytoplasm, which contains darkNet-19 as a basenetwork of the YOLOv2 model. In this model features are extracted from LeakyReLU-18 of darkNet-19 and supplied as an input to the YOLOv2 model. The YOLOv2-Nucleus-Cytoplasm model localizes and classifies the WBCs with maximum score labels. It also localize the WBCs into the blast and non-blast cells. After localization, the bag-of-features are extracted and optimized by using particle swarm optimization(PSO). The improved feature vector is fed to classifiers i.e., optimized naïve Bayes (O-NB) & optimized discriminant analysis (O-DA) for WBCs classification. The experiments are performed on LISC, ALL-IDB1, and ALL-IDB2 datasets.
Languageen
PublisherIEEE
SubjectCytoplasm
DarkNet-19
Leukocytes
Recognition
White blood cells
YOLOv2
TitleRecognition of different types of leukocytes using YOLoV2 and optimized bag-of-features
TypeArticle
Pagination167448-167459
Volume Number8
dc.accessType Open Access


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record